Package org.apache.druid.query.operator.window

Interface Processor

All Known Implementing Classes:
ComposingProcessor, WindowCumeDistProcessor, WindowDenseRankProcessor, WindowFirstProcessor, WindowFramedAggregateProcessor, WindowLastProcessor, WindowOffsetProcessor, WindowPercentileProcessor, WindowRankingProcessorBase, WindowRankProcessor, WindowRowNumberProcessor, WindowValueProcessorBase
public interface Processor
A Processor is a bit of logic that processes a single RowsAndColumns object to produce a new RowsAndColumns object. Generally speaking, it is used to add or alter columns in a batch-oriented fashion.

This interface was created to support windowing functions, where the windowing function can be implemented assuming that each RowsAndColumns object represents one partition. Thus, the window function implementation can only need to worry about how to process a single partition at a time and something external to the window function worries about providing data with the correct partitioning.

Over time, it's possible that this interface is used for other purposes as well, but the fundamental idea of usages of the interface should always be doing a one-to-one transformation of RowsAndColumns objects. That is, it's a RowsAndColumns in and a RowsAndColumns out.

  • Method Details

    • process

      RowsAndColumns process(RowsAndColumns incomingPartition)
      Applies the logic of the processor to a RowsAndColumns object
      Parameters:
      incomingPartition - the incoming RowsAndColumns object
      Returns:
      the transformed RowsAndColumns object

    • validateEquivalent

      boolean validateEquivalent(Processor otherProcessor)
      Validates the equivalence of the Processors. This is similar to @{code .equals} but is its own method so that it can ignore certain fields that would be important for a true equality check. Namely, two Processors defined the same way but with different output names can be considered equivalent even though they are not equal.

      This primarily exists to simplify tests, where this equivalence can be used to validate that the Processors created by the SQL planner are actually equivalent to what we expect without needing to be overly dependent on how the planner names the output columns

      Parameters:
      otherProcessor - the processor to test equivalence of
      Returns:
      boolean identifying if these processors should be considered equivalent to each other.

    • getOutputColumnNames

      List<String> getOutputColumnNames()
      Returns:
      List of output column names for the Processor.